TY - CHAP
T1 - Virtual reality and sensors for the next generation medical systems
AU - Mata, Félix
AU - Torres-Ruiz, Miguel
AU - Zagal-Flores, Roberto
AU - Moreno-Ibarra, Marco
N1 - Publisher Copyright:
© 2020 Elsevier Inc. All rights reserved.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - In this chapter, a case study where virtual reality (VR) considers a diverse type of sensors for the next generation of medical applications is presented. A VR system focused on the medical context applying human interfaces for the examination and treatment of back diseases caused by obesity or overweight is described. It is a framework that allows a patient to observe in a virtual model a prediagnosis of the health status related to his back, for later medical evaluation. The use of human interfaces combined with VR represents an innovation in the field of Health Informatics. Additionally, information is provided to some of the harmful effects of obesity on the lumbar spine compared versus the ideal state that it would have. So a virtual model shows the complications that could arise if the patient is not treated. The proposed health profile of the patient indicates diseases related to the current posture and the condition of his back. It also presents what posture must have the patient to keep the back in good health. The research is performed by using human interfaces and VR technology. In this case, human interfaces analyze the postural examination, while the VR technology allows both the patient and the physician to review in a digital representation the results of the postural analysis. Moreover, a semantic module is proposed to generate recommendations in order to improve the posture, while an animated sequence is displayed to observe the movement and possible anomalies when a patient is walking. Thus the problems detected within a virtual scenario are pointed out. This system allows the patient to have a graphical and prediagnostic representation of the health of his back; taking into account that a subsequent medical assessment is required. The obtained outcomes were compared against data from physical and radiography examinations, showing a performance of 80% of effectiveness in a sample of 50 patients.
AB - In this chapter, a case study where virtual reality (VR) considers a diverse type of sensors for the next generation of medical applications is presented. A VR system focused on the medical context applying human interfaces for the examination and treatment of back diseases caused by obesity or overweight is described. It is a framework that allows a patient to observe in a virtual model a prediagnosis of the health status related to his back, for later medical evaluation. The use of human interfaces combined with VR represents an innovation in the field of Health Informatics. Additionally, information is provided to some of the harmful effects of obesity on the lumbar spine compared versus the ideal state that it would have. So a virtual model shows the complications that could arise if the patient is not treated. The proposed health profile of the patient indicates diseases related to the current posture and the condition of his back. It also presents what posture must have the patient to keep the back in good health. The research is performed by using human interfaces and VR technology. In this case, human interfaces analyze the postural examination, while the VR technology allows both the patient and the physician to review in a digital representation the results of the postural analysis. Moreover, a semantic module is proposed to generate recommendations in order to improve the posture, while an animated sequence is displayed to observe the movement and possible anomalies when a patient is walking. Thus the problems detected within a virtual scenario are pointed out. This system allows the patient to have a graphical and prediagnostic representation of the health of his back; taking into account that a subsequent medical assessment is required. The obtained outcomes were compared against data from physical and radiography examinations, showing a performance of 80% of effectiveness in a sample of 50 patients.
KW - Health profile
KW - Human interface
KW - Medical assessment
KW - Postural analysis
KW - Prediagnostic representation
KW - Semantic recommendations
UR - http://www.scopus.com/inward/record.url?scp=85093489013&partnerID=8YFLogxK
U2 - 10.1016/B978-0-12-819043-2.00012-5
DO - 10.1016/B978-0-12-819043-2.00012-5
M3 - Capítulo
AN - SCOPUS:85093489013
SP - 279
EP - 303
BT - Innovation in Health Informatics
PB - Elsevier
ER -